






'''simple docstring'''







from __future__ import annotations

from typing import Any




class   __SCREAMING_SNAKE_CASE       :


  """simple docstring"""


  def __init__(			self   ,	UpperCamelCase__   ,	UpperCamelCase__   ,	UpperCamelCase__ = 0	):






         """simple docstring"""


         a_     ,	a_						     =			row, column
         a_						     =			[[default_value for c in range(UpperCamelCase__	)] for r in range(UpperCamelCase__	)]







  def __str__(			self	):






         """simple docstring"""


         a_						     =			f'Matrix consist of {self.row} rows and {self.column} columns\n'

         # Make string identifier
         a_						     =			0
         for row_vector in self.array:
                for obj in row_vector:
                       a_						     =			max(UpperCamelCase__   ,	len(str(UpperCamelCase__	)	)	)
         a_						     =			f'%{max_element_length}s'

         # Make string and return
         def single_line(UpperCamelCase__	) -> str:
                nonlocal string_format_identifier
                a_						     =			'['
                line += ", ".join(string_format_identifier % (obj,) for obj in row_vector	)
                line += "]"
                return line

         s += "\n".join(single_line(UpperCamelCase__	) for row_vector in self.array	)
         return s







  def __repr__(			self	):






         """simple docstring"""


         return str(self	)







  def    _a       (			self   ,	UpperCamelCase__	):






         """simple docstring"""


         if not (isinstance(UpperCamelCase__   ,	(list, tuple)	) and len(UpperCamelCase__	) == 2):
                return False
         elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
                return False
         else:
                return True







  def __getitem__(			self   ,	UpperCamelCase__	):






         """simple docstring"""


         assert self.validate_indicies(UpperCamelCase__	)
         return self.array[loc[0]][loc[1]]







  def __setitem__(			self   ,	UpperCamelCase__   ,	UpperCamelCase__	):






         """simple docstring"""


         assert self.validate_indicies(UpperCamelCase__	)
         a_						     =			value







  def __add__(			self   ,	UpperCamelCase__	):






         """simple docstring"""


         assert isinstance(UpperCamelCase__   ,	UpperCamelCase__	)
         assert self.row == another.row and self.column == another.column

         # Add
         a_						     =			Matrix(self.row   ,	self.column	)
         for r in range(self.row	):
                for c in range(self.column	):
                       a_						     =			self[r, c] + another[r, c]
         return result







  def __neg__(			self	):






         """simple docstring"""


         a_						     =			Matrix(self.row   ,	self.column	)
         for r in range(self.row	):
                for c in range(self.column	):
                       a_						     =			-self[r, c]
         return result







  def __sub__(			self   ,	UpperCamelCase__	):






         """simple docstring"""


         return self + (-another)







  def __mul__(			self   ,	UpperCamelCase__	):






         """simple docstring"""


         if isinstance(UpperCamelCase__   ,	(int, float)	):  # Scalar multiplication
                a_						     =			Matrix(self.row   ,	self.column	)
                for r in range(self.row	):
                       for c in range(self.column	):
                              a_						     =			self[r, c] * another
                return result
         elif isinstance(UpperCamelCase__   ,	UpperCamelCase__	):  # Matrix multiplication
                assert self.column == another.row
                a_						     =			Matrix(self.row   ,	another.column	)
                for r in range(self.row	):
                       for c in range(another.column	):
                              for i in range(self.column	):
                                     result[r, c] += self[r, i] * another[i, c]
                return result
         else:
                a_						     =			f'Unsupported type given for another ({type(UpperCamelCase__	)})'
                raise TypeError(UpperCamelCase__	)







  def    _a       (			self	):






         """simple docstring"""


         a_						     =			Matrix(self.column   ,	self.row	)
         for r in range(self.row	):
                for c in range(self.column	):
                       a_						     =			self[r, c]
         return result







  def    _a       (			self   ,	UpperCamelCase__   ,	UpperCamelCase__	):






         """simple docstring"""


         assert isinstance(UpperCamelCase__   ,	UpperCamelCase__	) and isinstance(UpperCamelCase__   ,	UpperCamelCase__	)
         assert self.row == self.column == u.row == v.row  # u, v should be column vector
         assert u.column == v.column == 1  # u, v should be column vector

         # Calculate
         a_						     =			v.transpose()
         a_						     =			(v_t * self * u)[0, 0] + 1
         if numerator_factor == 0:
                return None  # It's not invertable
         return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":


  def       __UpperCamelCase					(      ):
         """simple docstring"""




         a_						     =			Matrix(3   ,       3   ,       0   )
         for i in range(3   ):
                a_						     =			1
         print(F'a^(-1) is {ainv}'   )
         # u, v
         a_						     =			Matrix(3   ,       1   ,       0   )
         a_     ,	a_     ,	a_						     =			1, 2, -3
         a_						     =			Matrix(3   ,       1   ,       0   )
         a_     ,	a_     ,	a_						     =			4, -2, 5
         print(F'u is {u}'   )
         print(F'v is {v}'   )
         print(F'uv^T is {u * v.transpose()}'   )
         # Sherman Morrison
         print(F'(a + uv^T)^(-1) is {ainv.sherman_morrison(lowercase_   ,       lowercase_   )}'   )


  def       __UpperCamelCase					(      ):
         """simple docstring"""




         import doctest

         doctest.testmod()
  testa()












'''simple docstring'''







import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class   __SCREAMING_SNAKE_CASE       (__A       ):


  """simple docstring"""


  _a  : List[Any]      			=     ['''image_processor''', '''tokenizer''']
  _a  : List[Any]      			=     '''ViTImageProcessor'''
  _a  : int      			=     ('''CLIPTokenizer''', '''CLIPTokenizerFast''')







  def __init__(			self   ,	UpperCamelCase__=None   ,	UpperCamelCase__=None   ,	**UpperCamelCase__	):






         """simple docstring"""


         a_						     =			None
         if "feature_extractor" in kwargs:
                warnings.warn(
                    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                    ' instead.'   ,	UpperCamelCase__   ,	)
                a_						     =			kwargs.pop('feature_extractor'	)

         a_						     =			image_processor if image_processor is not None else feature_extractor
         if image_processor is None:
                raise ValueError('You need to specify an `image_processor`.'	)
         if tokenizer is None:
                raise ValueError('You need to specify a `tokenizer`.'	)

         super().__init__(UpperCamelCase__   ,	UpperCamelCase__	)







  def __call__(			self   ,	UpperCamelCase__=None   ,	UpperCamelCase__=None   ,	UpperCamelCase__=None   ,	UpperCamelCase__=None   ,	**UpperCamelCase__	):






         """simple docstring"""


         if text is None and visual_prompt is None and images is None:
                raise ValueError('You have to specify either text, visual prompt or images.'	)

         if text is not None and visual_prompt is not None:
                raise ValueError('You have to specify exactly one type of prompt. Either text or visual prompt.'	)

         if text is not None:
                a_						     =			self.tokenizer(UpperCamelCase__   ,	return_tensors=UpperCamelCase__   ,	**UpperCamelCase__	)

         if visual_prompt is not None:
                a_						     =			self.image_processor(UpperCamelCase__   ,	return_tensors=UpperCamelCase__   ,	**UpperCamelCase__	)

         if images is not None:
                a_						     =			self.image_processor(UpperCamelCase__   ,	return_tensors=UpperCamelCase__   ,	**UpperCamelCase__	)

         if visual_prompt is not None and images is not None:
                a_						     =			{
                    'pixel_values': image_features.pixel_values,
                    'conditional_pixel_values': prompt_features.pixel_values,
                }
                return encoding
         elif text is not None and images is not None:
                a_						     =			image_features.pixel_values
                return encoding
         elif text is not None:
                return encoding
         elif visual_prompt is not None:
                a_						     =			{
                    'conditional_pixel_values': prompt_features.pixel_values,
                }
                return encoding
         else:
                return BatchEncoding(data=dict(**UpperCamelCase__	)   ,	tensor_type=UpperCamelCase__	)







  def    _a       (			self   ,	*UpperCamelCase__   ,	**UpperCamelCase__	):






         """simple docstring"""


         return self.tokenizer.batch_decode(*UpperCamelCase__   ,	**UpperCamelCase__	)







  def    _a       (			self   ,	*UpperCamelCase__   ,	**UpperCamelCase__	):






         """simple docstring"""


         return self.tokenizer.decode(*UpperCamelCase__   ,	**UpperCamelCase__	)







  @property
  def    _a       (			self	):






         """simple docstring"""


         warnings.warn(
             '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'   ,	UpperCamelCase__   ,	)
         return self.image_processor_class







  @property
  def    _a       (			self	):






         """simple docstring"""


         warnings.warn(
             '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'   ,	UpperCamelCase__   ,	)
         return self.image_processor




